Computer Science – Information Theory
Scientific paper
2008-11-06
Computer Science
Information Theory
Scientific paper
Classical ML decoders of MIMO systems like the sphere decoder, the Schnorr-Euchner algorithm, the Fano and the stack decoders suffer of high complexity for high number of antennas and large constellation sizes. We propose in this paper a novel sequential algorithm which combines the stack algorithm search strategy and the sphere decoder search region. The proposed decoder that we call the Spherical-Bound-Stack decoder (SB-Stack) can then be used to resolve lattice and large size constellations decoding with a reduced complexity compared to the classical ML decoders. The SB-Stack decoder will be further extended to support soft-output detection over linear channels. It will be shown that the soft SB-Stack decoder outperforms other MIMO soft decoders in term of performance and complexity.
Ben-Othman Ghaya Rekaya
Ouertani Rym
Salah Abdellatif
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